Evaluate advances in information retrieval, NLP, and large language models; adapt the most promising approaches to enterprise data and product needs. Modernize the search stack for agentic and traditional search. Develop and improve sparse and dense retrieval methods, enterprise-adapted models, and query-understanding techniques. Work with engineering and platform teams to bring effective approaches into production at scale. Define and measure what better retrieval means. Use representative datasets, rigorous offline evaluation, statistical analysis, and production experiments to identify quality gaps, test hypotheses, understand model behavior, and communicate results that guide product decisions. Own research-backed solutions from problem formulation through deployment. Balance relevance, latency, and efficiency; monitor deployed models against quality and performance expectations; and iterate when results or data change. Provide scientific leadership across disciplines. Partner with product, engineering, and research teams to shape priorities, share practical advances, and mentor less experienced scientists. Document methods and findings, and contribute to publications or intellectual property where appropriate. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) These requirements include but are not limited to the following specialized security screenings: Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers). Experience presenting at conferences or other events in the outside research/industry community as an invited speaker. 3+ years experience conducting research as part of a research program (in academic or industry settings). 1+ year(s) experience developing and deploying live production systems, as part of a product team. 1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping. Experience with agentic search, including query planning, iterative retrieval, evidence selection, and evaluating the quality and efficiency of grounded responses. Experience applying machine learning to information retrieval, search relevance, or related retrieval problems. Experience shipping and evaluating deep-learning models in production at scale, including diagnosing quality or performance regressions. Solid programming skills in Python and experience with a modern deep-learning framework such as PyTorch. Experience designing offline evaluations and interpreting online experiments to make product decisions. Ability to lead an ambiguous technical problem and collaborate with engineering and product teams to deliver a solution.